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How people spend their time is an indicator of how they live their lives, with time use over the life course conditioned both by age and by participation in age-graded institutions. This chapter uses nationally representative data from the pooled 2008–2020 American Time Use Survey (ATUS) to evaluate how time use in 12 activity categories varies by age, gender, and disability status among 137,266 respondents aged 15 and older. By doing so, we quantify the “disability gap” in time use between men and women with and without disabilities, identifying at what age and by how much people with disabilities experience time differentials in activities of daily living (ADLs), instrumental activities of daily living (IADLs), and other indicators of social participation. Results indicate that – at many ages – patterns of time use for people with disabilities deviate from those of people without disabilities, with more pronounced differences in midlife. Further, the magnitude of women's disability gaps equals or exceeds men's for sleeping, and nearly all ADLs and IADLs, indicating that disability gaps are also gendered.

This study aims to investigate the factors that affect an audience's purchase decisions on a new type of social media, namely live video streaming platforms.

This study is based on data from an online survey providing 488 valid responses. These responses are used to test the research model by employing partial least squares (PLS) modeling.

Three antecedents (consumer competitive arousal, gift design aesthetics and broadcaster's image) influence the audience's purchase decisions (impulse buying and continuous buying intention). Chinese impression management (mianzi) acts as a moderator. Self-mianzi, mutual mianzi and other mianzi (i.e. three subtypes of mianzi) moderate the effects of consumer competitive arousal, gift design aesthetics and broadcaster's image on impulse buying.

The findings encourage practitioners developing marketing strategies for live video streaming platforms in the Chinese cultural context to consider peer influence, gift appearance, broadcaster's image and mianzi.

Drawing on the community gift-giving model and face-negotiation theory, this study provides an integrated research model to investigate a new type of social media (live video streaming). It offers insight into virtual gifting behaviors by confirming the effects of three antecedents on the audience's purchase decisions, with mianzi acting as a moderator.

In this chapter, we present two examples of research projects aimed at amplifying voices that are often silenced in research: those of children and/or youth from refugee backgrounds. Refugees are often excluded from research for both ethical and practical reasons: because of their assumed vulnerability as well as the challenges related to language or access. In the research projects presented, we aimed to employ methods that suited these groups of children and youth to understand their experiences in ways that they wanted to express them, and in situ. We argue that starting from, and finishing with, the point of view of the knowledge holders illustrates one means (although not exclusively so) by which to amplify their voices and knowledge to counter epistemic injustice in educational research.

The literature on help-seeking at work has experienced significant growth in the past decades. However, our knowledge about this research domain remains fragmented and lacks sufficient theoretical integration. Therefore, this paper aims to comprehensively integrate the extant literature on help-seeking behavior at work and propose an overarching, organized framework to propel this field forward.

A state-of-the-art review and theoretical development on help-seeking at work are conducted.

First, the authors provide the conceptual clarity of its definitions, key characteristics, types and measurement techniques. Second, the authors develop a fine-grained and integrative process-based framework consisting of antecedents, proximal psychological mechanisms, subsequent influencing processes and distal outcomes to advance our understanding of seeking help in the workplace. Third, the authors offer a detailed agenda for future research to target opportunities within the field.

The current study is comprehensive in surveying the full body of knowledge on help-seeking at work. It uniquely provides a coherent overarching framework that organizes prior findings and channels future research. Additionally, this review paints a complete picture of what has been done and what needs to be done in the field. More research can be spurred based on our conceptual framework.

This paper aims to propose an effective dynamic calibration and compensation method to solve the problem that the statically calibrated force sensor would produce large dynamic errors when measuring dynamic signals.

The dynamic characteristics of the force sensor are analyzed by modal analysis and negative step dynamic force calibration test, and the dynamic mathematical model of the force sensor is identified based on a generalized least squares method with a special whitening filter. Then, a compensation unit is constructed to compensate the dynamic characteristics of the force measurement system, and the compensation effect is verified based on the step and knock excitation signals.

The dynamic characteristics of the force sensor obtained by modal analysis and dynamic calibration test are consistent, and the time and frequency domain characteristics of the identified dynamic mathematical model agree well with the actual measurement results. After dynamic compensation, the dynamic characteristics of the force sensor in the frequency domain are obviously improved, and the effective operating frequency band is widened from 500 Hz to 1,560 Hz. In addition, in the time domain, the rise time of the step response signal is reduced from 0.29 ms to 0.17 ms, and the overshoot decreases from 26.6% to 9.8%.

An effective dynamic calibration and compensation method is proposed in this paper, which can be used to improve the dynamic performance of the strain-gauge-type force sensor and reduce the dynamic measurement error of the force measurement system.

This study aims to provide an understanding of how directors perceive the relationship between board independence and corporate social responsibility (CSR) performance which has remained under-researched.

The qualitative data were collected through semi-structured interviews of 19 directors from 14 organisations operating in Australia. Data were analysed following the six-phase process of thematic analysis.

The findings indicate that independent directors contribute to board CSR decisions in two major ways: they bring an outsider view to the board, and they monitor managers in taking decisions that consider the interests of the broader stakeholder groups.

The in-depth analysis of director independence and CSR highlights the structural and behavioural aspects of director independence and CSR playing out in board rooms. Propositions are offered which can be tested to advance the research in this arena.

The findings suggest that efforts are required at organisational policy level to ensure the effectiveness of director independence for CSR.

This study provides insights into the “black box” of boardroom dynamics highlighting important contextual factors influencing director independence and CSR decisions previously under-explored.

Teachers are an adaptive group of professionals and in this chapter, we explore the ways that teachers can develop themselves as leaders, even in the absence of strong support or leadership. We explore the manner that these skill sets and strengths can be cultivated, providing lived examples of how the authors have developed themselves. The ways that teachers can follow in the footsteps of the authors is outlined in clearly defined steps. By drawing on previous literature, we provide seven strong claims of developing middle leadership knowledge and skill sets beyond your school. Much of this development and community development work that develops and sharpens leadership skills can be explored through online fora and social media tools. These tools allow skill development, professional learning, and exposure to a broad range of education stakeholders and groups; for future pathways in school leadership roles and leading beyond school gate.

The purpose of this paper is to explore the significance impact of air quality as a contributing factor on residential property rents by applying geo-informatics to economic issues. Since air pollution poses a severe health threat, city residents should have a right to know about the (invisible) hazards they are exposed to.

Within spatial-temporal modeling of air pollutants in Berlin, Germany, three interpolation techniques are tested. The most suitable one is selected to create seasonal maps for 2018 and 2021 with pollution concentrations for particulate matter values and nitrogen dioxide for each 1,000 m² cell within the administrative boundaries. Based on the evaluated pollution particulate matter values, which are used as additional variables for semi-parametric regressions the impact of the air quality on rents is estimated.

The findings reveal a compelling association between air quality and the economic aspect of the residential real estate market, with noteworthy implications for both tenants and property investors. The relationship between air pollution variables and rents is statistically significant. However, there is only a “willingness-to- pay” for low particulate matter values, but not for nitrogen dioxide concentrations. With good air quality, residents in Berlin are willing to pay a higher rent (3%).

These results suggest that a “marginal willingness-to-pay” occurs in a German city. The research underscores the multifaceted impact of air quality on the residential rental market in Berlin. The evidence supports the notion that a cleaner environment not only benefits human health and the planet but also contributes significantly to the economic bottom line of property investors.

The paper has a unique data engineering approach. It collects spatiotemporal data from network of state-certified measuring sites to create an index of air pollution. This spatial information is merged with residential listings. Afterward non-linear regression models are estimated.